Quarantine restrictions provide an essential tool in the response to incursions of threatening pests and pathogens. The theoretical underpinnings of quarantine decisions, however, tend to be less well developed than those for surveillance. We simulate plant pathogen spread and control over a regional scale, to identify smart quarantine decisions. Our model is based on the current Queensland incursion of Panama disease Tropical Race 4, a fungal pathogen of bananas, but maintains sufficient generality to apply to other fungal species. The model includes within-property pathogen growth, and anthropogenic and environmental spread through multiple risk networks. We model diverse quarantine approaches, from easily implementable heuristic rules, to ones that attempt to exploit the structure of risk networks. We also allow for some level of “leakage” or small-level failure of quarantine restrictions. We contrast the performance of the different quarantine approaches in the context of relative importance of the different connectivity networks. Overall we find that a mix of long-distance as well as locally-focussed quarantine interventions is necessary to control spread and minimise the long-term impact of the incursion. This echoes recent results for optimal surveillance while focussing on prevention, rather than detection, of spread.